Metadata-Version: 2.4
Name: autoeda-sujay
Version: 0.1.0
Summary: Automated exploratory data analysis with one function call
Home-page: https://github.com/stormysujay2002/autoeda-sujay
Author: Sujay Das
Author-email: stormysujay2002@example.com
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: pandas>=1.3.0
Requires-Dist: numpy>=1.20.0
Requires-Dist: matplotlib>=3.3.0
Requires-Dist: seaborn>=0.11.0
Provides-Extra: dev
Requires-Dist: pytest>=6.0; extra == "dev"
Requires-Dist: black; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: provides-extra
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# AutoEDA - Automated Exploratory Data Analysis

One function call for comprehensive data analysis and visualization.

## Installation

### Local Development Installation

\`\`\`bash
# Clone or download this project
# Navigate to the project directory
cd autoeda-library

# Install in development mode
pip install -e .
\`\`\`

## Quick Start

```python
import pandas as pd
import autoeda

# Load your data
df = pd.read_csv('your_data.csv')

# One function call does everything!
report = autoeda.analyze(df)

# View summary
report.show_summary()

# Generate visualizations
report.plot_missing_data()
report.plot_distributions()
report.plot_correlation_matrix()
